A Method for Registration of 3D SurfacesICP Algorithm

Erhan Avinal

Introduction

Building 3D models of real world objects Data capture using range camera Registration Data merge

Registration - Goal

To transform sets of surface measurements into a common coordinate system

A model shape and a data shape

Registration

If we know correct correspondences, we can find correct translation and rotation

Registration

Issue : Finding corresponding points ICP : Assume closest points correspond to

each other, compute the best transform

Rotation and translation

ICP Algorithm

Can be used with

Distance

Euclidian distances

Point to point set

Point to line segment

Point to triangle

Point to parametric entity

Point to implicit entity

Algorithm

Point Set P with Np points, model shape X Iterate until convergence

Compute closest points Squared Euclidian distances

Compute registration (rotation and translation) Apply the registration

New point set

Other Issues

Color matching Sharp, 2002 Godin, 1995 Johnson, 1997

Orientation Godin 2001 Schutz 1998

Other Issues

Weighting Important nodes

Initial point selection Uniform sampling Random Select in regions of high curvature

k-d trees to find closest points

Results

Results

Results

Results

Results

Conclusions

ICP can register a data shape to a model shape

Independent of shape representation Does not require preprocessing of 3D data A good initial estimate of transformation is

required High computation cost

Future Work

Computational speedup Parallel testing Allow deformations

References

Original Paper: P.J. Besl, N.D. McKay,A Method of Registration of 3D

Shapes, 1992 T. Jost, Fast Geometric Matching for Shape

Registration, 2002 S.M. Rusinkiewicz, Real time Acquisition and

Rendering of Large 3D Models, 2001 http://www.ee.surrey.ac.uk/Research/VSSP/3DVisio

n/model_building/model.html

Thanks